• Smart Structures and Systems
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• v.29 no.2
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.17-24
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• 2004

In this paper, the wavelet video coding using Low-Band-Shift(LBS) method and multiresolution motion estimation(MRME) is proposed. To overcome shift- variant property on wavelet coefficients, the LBS was proposed. LBS method previously has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. Therefore to reduce computational complexity of video coding using LBS, we combine MRME with LBS. When mm is applied only, it has 7 times as much as existing method's motion vector because each subband has different motion vector using property of LBS, number of motion vector decreases. Proposed method decreases motion vector, and it decreases motion compensated Prediction error by detailed motion estimation. And then it shows better coding performance. Also this method reduces computational amount by smaller search area in higher resolution. The computational complexity of the proposed method is 12.1% of that of existing method at 3-level wavelet transform. The experimental results with the proposed method show about 0.2∼9.7% improvement of MAD performance in case of lossless coding, and 0.1∼2.0㏈ improvement of PSNR performance at 4he same bit rate in case of lossy coding.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.110-120
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• 2003

In this paper, we propose a Multiresolution Motion Estimation(MRME) adapted to Low-Band-Shift(LBS) method in wavelet domain. To overcome shift-variant property on wavelet coefficients, the LBS was previously proposed. This method which is applied to reference frame in video coding technique, has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. In this paper, The computational complexity of the proposed method(LBS-MRME) is about 15.6% of that of existing method at 3-level wavelet transform. And although it has about 7 times as much as existing method's motion vector since each subband has different motion vector, it decreases motion compensated prediction error by detailed motion estimation, and then has better efficient coding performance. The experimental results with the proposed method showed about 0.3∼11.6% improvement of MAD performance in case of lossless coding, and 0.3∼3.0㏈ improvement of PSNR performance at the same bit rate in case of lossy coding.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1455-1461
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• 2012

MIMO-OFDM which is one of core techniques for the high-speed mobile communication system requires the efficient channel estimation method with low estimation error and computational complexity, for accurately receiving data. In this paper, we propose a channel estimation algorithm with low channel estimation error comparing with LS which is primarily employed to the MIMO-OFDM system, and with low computational complexity comparing with MMSE. The proposed algorithm estimates channel vectors based on the LMS adaptive algorithm in the time domain, and the estimated channel vector is sent to the detector after FFT. We also suggest a preamble architecture for the proposed MIMO-OFDM channel estimation algorithm. The computer simulation example is provided to illustrate the performance of the proposed algorithm.

• ETRI Journal
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• v.38 no.1
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• pp.100-111
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• 2016

This paper presents a low-complexity channel-adaptive reconfigurable $4{\times}4$ QR-decomposition and M-algorithm-based maximum likelihood detection (QRM-MLD) multiple-input and multiple-output (MIMO) detector. Two novel design approaches for low-power QRM-MLD hardware are proposed in this work. First, an approximate survivor metric (ASM) generation technique is presented to achieve considerable computational complexity reduction with minor BER degradation. A reconfigurable QRM-MLD MIMO detector (where the M-value represents the number of survival branches in a stage) for dynamically adapting to time-varying channels is also proposed in this work. The proposed reconfigurable QRM-MLD MIMO detector is implemented using a Samsung 65 nm CMOS process. The experimental results show that our ASM-based QRM-MLD MIMO detector shows a maximum throughput of 288 Mbps with a normalized power efficiency of 10.18 Mbps/mW in the case of $4{\times}4$ MIMO with 64-QAM. Under time-varying channel conditions, the proposed reconfigurable MIMO detector also achieves average power savings of up to 35% while maintaining a required BER performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.868-874
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• 2007

A real-time frame-layer rate control algorithm with a token bucket traffic shaper is proposed for minimizing video duality variation. The proposed rate control method uses a non-iterative optimization method for low computational complexity, and performs bit allocation at the frame level to minimize variation in distortion between frames. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce the delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better PSNR performance than the existing rate control method.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.1048-1056
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• 1998

In this paper, a fractal image coding based on discrete wavelet transform is proposed to improve PSNR at low bit rates and reduce computational complexity of encoding process. The proposed method takes the absolute value of discrete wavelet transform coefficients, and then constructs significant coefficients trees, which indicate the positions and signs of the significant coefficients. This method improves PSNR and reduces computational complexity of mapping contracted domain pool onto range block, by matching only the significant coefficients of range block to coefficients of contracted domain block. Also, this paper proposes a classification scheme which minimizes the number of contracted domain blocks compared with range block. This scheme significantly reduces the number of range and contracted domain block comparison.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2708-2721
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• 2014

Data outsourcing in the cloud (DOC) is a promising solution for data management at the present time, but it could result in the disclosure of outsourced data to unauthorized users. Therefore, protecting the confidentiality of such data has become a very challenging issue. The conventional way to achieve data confidentiality is to encrypt the data via asymmetric or symmetric encryptions before outsourcing. However, this is computationally inefficient because encryption/decryption operations are time-consuming. In recent years, a few DOC schemes based on secret sharing have emerged due to their low computational complexity. However, Dautrich and Ravishankar pointed out that most of them are insecure against certain kinds of collusion attacks. In this paper, we proposed a novel DOC scheme based on Shamir's secret sharing to overcome the security issues of these schemes. Our scheme can allow an authorized data user to recover all data files in a specified subset at once rather than one file at a time as required by other schemes that are based on secret sharing. Our thorough analyses showed that our proposed scheme is secure and that its performance is satisfactory.

• Convergence Security Journal
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• v.3 no.2
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• pp.33-40
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• 2003

The biggest problem for the oblivious transfer protocol is the rapid increasement of network traffic and computational complexity if the protocol is used as a sub-protocol compare to the case that when it is used as a standalone protocol. To fix such problems, in this paper, we propose a verifiable Non-interactive OT protocol that reduces the network traffic and computational complexity by preprocessing the necessary computations when the network traffic is low. The proposed protocol uses third root mechanism instead of square root mechanism that is used for the Fiat-Shamir signature mechanism and also uses 1-out-of-2 oblivious transfer based on signature mechanism. We also analyze the proposed protocol by comparing to the Lein Harn, YNIOT protocols.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.846-856
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• 2016

Wireless sensor networks (WSNs) are widely applied in monitoring and control of environment parameters. It is sometimes necessary to disseminate data through wireless links after they are deployed in order to adjust configuration parameters of sensors or distribute management commands and queries to sensors. Several approaches have been proposed recently for data dissemination in WSNs. However, none of these approaches achieves both high efficiency and low complexity simultaneously. To address this problem, cluster-tree based network architecture, which divides a WSN into hierarchies and clusters is proposed. Upon this architecture, data is delivered from base station to all sensors in clusters hierarchy by hierarchy. In each cluster, father broadcasts data to all his children with instantly decodable network coding (IDNC), and a novel scheme targeting to maximize total transmission gain (MTTG) is proposed. This scheme employs a new packet scheduling algorithm to select IDNC packets, which uses weight status feedback matrix (WSFM) directly. Analysis and simulation results indicate that the transmission efficiency approximate to the best existing approach maximum weight clique, but with much lower computational overhead. Hence, the energy efficiency achieves both in data transmission and processing.